International Journal of Epidemiology 2000;29:975-982
© International Epidemiological Association 2000
Joint effects of nine polychlorinated biphenyl (PCB) congeners on breast cancer risk
a Department of Epidemiology and Public Health, Yale University School of Medicine, New Haven, CT, USA.
b National Cancer Institute, Bethesda, MD, USA.
c Department of Environmental Health, Colorado State University, Fort Collins, CO, USA.
d European Institute of Oncology, Milan, Italy.
Reprint requests: Dr Theodore R Holford, Department of Epidemiology and Public Health, Yale University School of Medicine, 60 College Street, PO Box 208034, New Haven, CT 06520–8034, USA.
Background Polychlorinated biphenyls (PCB) have been a major environmental health concern because of their wide distribution and persistence in the environment. Estimating joint effects of all congeners in a single analysis is complicated by correlation among exposure levels, and the resulting collinearity makes the results difficult to interpret.
Methods Patients with breast-related surgery at Yale-New Haven Hospital were interviewed using a standardized questionnaire, and breast adipose tissue samples were analysed for nine PCB congeners (74, 118, 138, 153, 156, 170, 180, 183, 187). The study recruited 490 women (304 cases and 186 controls) between 1994 and 1997. Logistic ridge regression was used to analyse the instability caused by collinearity.
Results Although total PCB did not appear to be associated with breast cancer risk, significant differences in effect were observed among the nine congeners. Logistic ridge regression demonstrated a protective effect on breast cancer risk for a potentially anti-oestrogenic and dioxin-like congener, 156, while two phenobarbital, CYP1A and CYP2B inducers had an adverse effect, 180 and 183. This analysis also suggested that a protective effect for another phenobarbital congener, 153, was largely explained by instability caused by collinearity.
Conclusions These results indicate that studies of PCB congeners and health require an in-depth statistical analysis in order to better understand the complex issues related to their collinearity.
Keywords Breast cancer, environmental epidemiology, PCB, logistic regression, ridge regression
Accepted 16 May 2000
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